It felt great to finally attach the powered ragdoll rig to the planning rig.

A presentation I gave at the Computer Simulation And Gaming Conference (University of Tulsa) about my physically simulated character controller project.

An experimental demo is available at: http://digitalopus.ca/_uploads/PhysicsCharacterController.zip This version uses very large 512×3 layer models. The results are good, but I can realistically only run 1-2 characters per scene max. Much of the past few months has been spent reducing the model size. I now use 256×3 models with fewer observations. These models are 10x…

Here is an update on the progress of my ML efforts. Started training a giant colossus sized rig (30 meters tall). Finally upgraded to the latest version of ML Agents. Upgrading is something I generally do infrequently because it usually generates a lot of re-work, but there have been a lot of improvements added. One…

I added a stabilizer to help align the center of mass with the feet when airbourne. It is not physically realistic but makes the jumps much more reliable

Almost usable fully physically simulated experimental character controller. No animations. It has been trained to mimic animations, but needs to walk, balance, turn etc… while mimicking the animations. It can walk, run, jump, tumble & getup. It is awkward to use, some things that one takes for granted (predictable jumps, reliable landing) can be challenging.…

This has come a long way since my first attempt to train the guy to walk. Over the Christmas break I trained a tumbling brain so he can get up quickly if he falls with some velocity. Next steps: try to get this working with moving and accelerating platforms.